Add data for population aged 10 years and over by marital status and sex

[cliftonmcintosh]

Is this part of the census, @ravinepal ?

[tfungproj]

My first PR and I like to contribute. I found the dataset from Open Nepal. Please review: https://github.com/opennepal/odp-census/blob/master/Population%20aged%2010%20years%20and%20over%20by%20marital%20status,%20sex%20and%205%20years%20age%20group/data.csv?raw=true

[cliftonmcintosh]

@tfungproj

I believe that is indeed the data set for this issue, and we would welcome your contribution to NepalMap. Please feel free to claim this ticket.

Do you need any information or guidance on how to transform and integrate a data set into NepalMap? I will be happy to offer guidance or assistance when needed.

One request I have is that you would make public the tool or script you use to transform the data into the form needed for NepalMap. We have a set of scripts in the maptools project. Specifically, there is a directory for scripts for transforming OpenNepal's census data here. If you write a script for data transformation, can you submit a PR to have it included in that project? This provides transparency and reproducibility for our data transformations. Adapting or improving one of the current scripts to serve for transforming the marriage data is welcome as well.

[tfungproj]

@cliftonmcintosh

I will fork the project and start working on it. I see the python scripts in https://github.com/Code4Nepal/maptools/tree/master/opennepal/odpcensus/age.py. I can do something similar to that. How does that sound?
What is the format expected by NepalMap?
Also, I am not sure how to "claim" this ticket? Please advise.

thanks!

[cliftonmcintosh]

@tfungproj

That all sounds good. As far as claiming a ticket goes, there is a way to assign an issue to a user, but it appear that only applies to internal team members. Instead, I will remove the Help Wanted label on this issue.

Thanks for contributing. Please let me know if you have any questions or want any guidance.

[tfungproj]

@cliftonmcintosh
I am going need more guidance on how to start on it.

1. What is the final format to transform the data to? What are the fields or column headers?
2. Any detail on the code to get started will also be helpful.
   Thank you

[cliftonmcintosh]

@tfungproj

I believe the fields for this data set would be:
geo_level, geo_code, sex, "age group", "marital status", total

Here is what the first two columns in the data set would likely be turned into:
district,68,male,10-14,Never Married,19167
district,68,male,10-14,Single married,43

The geo_level for district-level data is district. The geo_level for the nation is data is country. The geo_code for each district is found in maptools/shared/geoidmappings.py, and the geo_code for Nepal is NP. There are examples in maptools showing how to find the geo_code based on the district names in the data set. The data at the country level is collected by totaling the data for the districts.

I'm not sure how this data gets visualized. You might look at South Africa's Wazimap or Kenya's Hurumap to get ideas of ways to present data sliced three ways ("sex", "age group" and "marital status").

Once a table is populated, you can choose to visualize by only some of the categories. For example, you might decide to display data only based on age group and marital status, not also splitting by sex. I'm not suggesting you should or should not do that. This is only an example of how to simplify for display purposes.

[cliftonmcintosh]

@tfungproj

I wanted to see whether this is still a data set you are interested in working on. If so, please let us know if there is any guidance or assistance we can provide.